Solving a Flexible Flow Shop Scheduling Problem Using a Hybrid Approach

In the context of manufacturing, scheduling is essential for the efficient use of resources in the production, which is optimal in terms of certain performance procedures. Referring on the production environment, scheduling problems can differ significantly. As an extension of the Flow shop scheduling problem, flexible or hybrid flow shop scheduling problem (FFSP) is considered as a typical manufacturing challenge in manufacturing systems for its difficulty and flexibility by allowing for a job to be processed on more than one machine. Owing to its high computational complexity, it is considered to be NP-hard optimization problem. In this paper, we propose a new approach using particle swarm optimization (PSO) and Jaya (JA) algorithm to solve FFSP. The objective is to achieve an optimum production schedule of jobs which would minimize the total completion time (makespan). The PSO algorithm is able of providing sufficient diversification during the search. In the other hand, JA algorithm is simple and efficient meta-heuristic optimization technique that has been effectively applied by various researchersin diverse fields of engineering and sciences. Experiments are made to verify the performance of the proposed algorithm compared to well-known approaches in the literature. Computational results reveal that the proposed approach can solve the problem under study with high efficiency.